Proud to announce BioMCP, an open source Model Context Protocol (MCP) server for biomedical research AI assistants and agents. BioMCP searches and retrieves clinical trials, PubMed articles and genomic variants to provide up-to-date and relevant context to an LLM.

Just everything else with AI, you can get good results with low effort.

Then you can grind and keep eeking out gains.

This has add’l benefits:
- improvement on that task
- greater vision of what else you can do
- higher expectations on what good results are
- better first drafts the next time.

Any research on the impact of JSON key sort order on generating structured outputs?

For instance, I do something like this:

- analyze
- draft
- evaluate
- final

And then provide exemplars with errors to show self correction.

But I haven’t done extensive testing. Just seems like a good idea.

Chat with any open source repo easily. Gitingest (free online tool) turns any GitHub repository into a single markdown file for pasting. Claude artifacts makes this 300k token output pretty easy to work with.

Nice paper from Databricks Mosaic Research that analyzes RAG performance with long-context LLMs. Lots of great data and insights about the leading models and how their performance improves or degrades as more content is added to the context window.

ArXiv Paper:
arxiv.org/pdf/2411.03538

I'm tracking the language models, libraries, and resources for generating structured outputs (JSON) on GitHub (2K stars). PRs welcome!

Repo:
github.com/imaurer/awes...

GLiREL is a zero-shot Relation Extraction (RE) model capable of classifying unseen relations given the entities within a text.

Builds upon GLiNER which does 0-shot Named Entity Recognition (NER).

Repo:
github.com/jackboyla/GL...

Model:
huggingface.co/jackboyla/gl...

h/t @pacoid.bsky.social